Lead Data Scientist

About the role

In this role you will contribute to the development and refinement of our data processing pipeline while shaping new analytical methodologies. You’ll grow from owning specific steps of the pipeline to becoming an expert across data cleaning, preparation, and rule validation, working fluently with Python and large datasets.

Key responsibilities

• Develop and improve the data processing pipeline and related analytical methods.
• Own specific pipeline steps and become an expert in data cleaning, preparation, and rule validation.
• Design new analytical methods, translate them into clear specifications, and collaborate with engineering teams for scalable implementation.
• Coordinate closely with stakeholders to gather requirements, ensure alignment, and deliver solutions that meet business needs.
• Support cross‑functional teams in production deployment and impact evaluation.

Required profile

• 5+ years of professional experience in data science or related fields.
• Master’s or Doctorate in Data Science, Mathematics, Statistics, or a related engineering discipline.
• Strong understanding of consumer behavior, panel‑based projections, and consumer analytics.
• Experience with crowdsourced panels, receipt capture methodologies, and large‑scale data sets.
• End‑to‑end mindset, connecting methodology, engineering, and business context.
• Excellent communication, collaboration, and continuous‑learning attitude.

Required skills

• Python programming (including statistical method implementation).
• PySpark for large‑scale data processing.
• SQL query development (optional).
• Cloud platforms such as Azure AI, Databricks, Snowflake.
• Version‑control systems like GitHub or Bitbucket.

What we offer

• Flexible working environment.
• Volunteer time off.
• LinkedIn Learning access.
• Employee Assistance Program (EAP).